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This is most useful for two subplots (e.g.: fig, (ax1, ax2) = plt.subplots(1, 2) or fig, (ax1, ax2) = plt.subplots(2, 1)). For more subplots, it's more efficient to flatten and iterate through the array of axes.
pyplot.subplots creates a figure and a grid of subplots with a single call, while providing reasonable control over how the individual plots are created. For more advanced use cases you can use GridSpec for a more general subplot layout or Figure.add_subplot for adding subplots at arbitrary locations within the figure.
10 cze 2023 · As of matplotlib 3.6.0, width_ratios and height_ratios can now be passed directly as keyword arguments to plt.subplots and subplot_mosaic, as per What's new in Matplotlib 3.6.0 (Sep 15, 2022). f, (a0, a1) = plt.subplots(1, 2, width_ratios=[3, 1]) f, (a0, a1, a2) = plt.subplots(3, 1, height_ratios=[1, 1, 3])
22 lip 2020 · Subplots mean groups of axes that can exist in a single matplotlib figure. subplots() function in the matplotlib library, helps in creating multiple layouts of subplots. It provides control over all the individual plots that are created.
See How to plot in multiple subplots for accessing and plotting in subplots. import matplotlib.pyplot as plt # create the figure with tight_layout=True fig, axes = plt.subplots(nrows=4, ncols=4, figsize=(8, 8), tight_layout=True)
Simple demo with multiple subplots. For more options, see Creating multiple subplots using plt.subplots . import matplotlib.pyplot as plt import numpy as np # Create some fake data. x1 = np . linspace ( 0.0 , 5.0 ) y1 = np . cos ( 2 * np . pi * x1 ) * np . exp ( - x1 ) x2 = np . linspace ( 0.0 , 2.0 ) y2 = np . cos ( 2 * np . pi * x2 )
7 lut 2020 · If you create a 2×1 grid, you have 2 rows and each row takes up 1/2 of the space. If you create a 3×2 grid, you have 6 subplots and each takes up 1/6 of the space. Using plt.subplots() you can create a 2×1 plot with 2 rows that take up any fraction of space you want.
